Integration of Statistical and Neural Network Method for Data Analysis
Krishna K Chavali
The issues that are to be considered while selecting data analysis methods are data
type and expected solution type. Incorrect selection of either can lead to incomplete
solution leading user taking an uninformed decision. The software developed for this
thesis (SANE - Statistical And NEural network data analysis) is aimed at enabling a user
to use advanced data analysis techniques to handle a given research issue. An
effective navigation system is designed for user to select the analysis method by
responding to a set of questions. SANE provides web based data analysis using
statistical and neural networks methods. The statistical analysis module has methods
for finding a relationship between variables, predicting group membership and finding
group differences. The neural net module has back propagation and cascade
correlation algorithms. Users can apply different methods on same dataset and
compare the results. This software is implemented in ASP.NET2.0 with backend in
SQL2005.